class_docstr: Post-processing methods for ABCNet.
  
  Args:
      num_classes (int): Number of classes.
      use_sigmoid_cls (bool): Whether to use sigmoid for classification.
      strides (tuple): Strides of each feature map.
      norm_by_strides (bool): Whether to normalize the regression targets by
          the strides.
      bbox_coder (dict): Config dict for bbox coder.
      text_repr_type (str): Text representation type, 'poly' or 'quad'.
      with_bezier (bool): Whether to use bezier curve for text detection.
      train_cfg (dict): Config dict for training.
      test_cfg (dict): Config dict for testing.
code: def __init__(
      self,
      text_repr_type="poly",
      rescale_fields=["beziers", "polygons"],
  ):
      super().__init__(
          text_repr_type=text_repr_type, rescale_fields=rescale_fields
      )
  
file_path: mmocr/projects/ABCNet/abcnet/model/abcnet_postprocessor.py
imports: from mmocr.models.textdet.postprocessors.base import BaseTextDetPostProcessor
  from mmocr.registry import MODELS
  from ..utils import bezier2poly
label_desc: Use image node_id 1 to create a new ABCNetPostprocessor object from inherited base classes: BaseTextDetPostProcessor with example: obj = ABCNetPostprocessor(text_repr_type, rescale_fields)